Modelling gut-feeling/subconscious knowledge of stock market traders
You could perhaps model gut feeling or subconscious bias as a prior in a Bayesian context, and then try to learn from the data how much to modify/moderate the bias in each individual case.

I think there is another issue with the problem you outlined.  We might expect it to be normal to see more losers than winners in the long run: trading is a zero-sum game where the house always takes its cut. The trick to being a successful trading algorithm seems to be to make the losers small (cut them early) and the winners big (let them run).